code: def __init__(
      self,
      preprocess: nn.Module,
      inference: nn.Module,
      postprocess: nn.Module,
  ) -> None:
      super().__init__()
      self.preprocess = preprocess
      self.inference = inference
      self.postprocess = postprocess
  
imports: import torch
  import torch.nn
  import warnings
  import random
  import numpy
  from torch.utils.data import TensorDataset, DataLoader
  import numpy
  import multiprocessing
  import warnings
  import math
label_desc: Use image node_id 1 to create a new ExportForecastingPipeline object from inherited base classes: nn with example: obj = ExportForecastingPipeline(preprocess, inference, postprocess)